Package: nn2poly 0.1.2

Pablo Morala

nn2poly: Neural Network Weights Transformation into Polynomial Coefficients

Implements a method that builds the coefficients of a polynomial model that performs almost equivalently as a given neural network (densely connected). This is achieved using Taylor expansion at the activation functions. The obtained polynomial coefficients can be used to explain features (and their interactions) importance in the neural network, therefore working as a tool for interpretability or eXplainable Artificial Intelligence (XAI). See Morala et al. 2021 <doi:10.1016/j.neunet.2021.04.036>, and 2023 <doi:10.1109/TNNLS.2023.3330328>.

Authors:Pablo Morala [aut, cre], Iñaki Ucar [aut], Jose Ignacio Diez [ctr]

nn2poly_0.1.2.tar.gz
nn2poly_0.1.2.tar.gz(r-4.5-noble)nn2poly_0.1.2.tar.gz(r-4.4-noble)
nn2poly_0.1.2.tgz(r-4.4-emscripten)nn2poly_0.1.2.tgz(r-4.3-emscripten)
nn2poly.pdf |nn2poly.html
nn2poly/json (API)
NEWS

# Install 'nn2poly' in R:
install.packages('nn2poly', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/ibidat/nn2poly/issues

Pkgdown site:https://ibidat.github.io

Uses libs:
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library

On CRAN:

Conda:

cppopenmp

3.54 score 1 stars 23 scripts 608 downloads 4 exports 5 dependencies

Last updated 4 months agofrom:4f87bea040. Checks:1 OK, 1 NOTE. Indexed: no.

TargetResultLatest binary
Doc / VignettesOKFeb 23 2025
R-4.5-linux-x86_64NOTEFeb 23 2025

Exports:add_constraintsfitluz_model_sequentialnn2poly

Dependencies:genericsmatrixStatspracmaRcppRcppArmadillo

Classification example using tensorflow

Rendered fromnn2poly-03-classification-example.Rmdusingknitr::rmarkdownon Feb 23 2025.

Last update: 2024-01-25
Started: 2024-01-25

Introduction to nn2poly

Rendered fromnn2poly-01-introduction.Rmdusingknitr::rmarkdownon Feb 23 2025.

Last update: 2024-11-11
Started: 2024-01-25

Supported DL frameworks

Rendered fromnn2poly-02-supported-DL-frameworks.Rmdusingknitr::rmarkdownon Feb 23 2025.

Last update: 2024-11-11
Started: 2024-01-25